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Erschienen in:
2010 | OriginalPaper | Buchkapitel
Learning a Fine Vocabulary
verfasst von : Andrej Mikulík, Michal Perdoch, Ondřej Chum, Jiří Matas
Erschienen in: Computer Vision – ECCV 2010
Verlag: Springer Berlin Heidelberg
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A novel similarity measure for bag-of-words type large scale image retrieval is presented. The similarity function is learned in an unsupervised manner, requires no extra space over the standard bag-of-words method and is more discriminative than both L2-based soft assignment and Hamming embedding.
We show experimentally that the novel similarity function achieves mean average precision that is superior to any result published in the literature on a number of standard datasets. At the same time, retrieval with the proposed similarity function is faster than the reference method.